Senior Machine Learning Engineer (Fraud)
Tasks
- Build feature pipelines and training datasets
- Collaborate with engineering analytics product and ML platform teams
- Communicate model performance and recommendations
- Develop fraud prediction models
- Ensure code quality with testing documentation and peer review
- Implement model retraining and backtesting workflows
- Improve machine learning development processes and infrastructure
- Integrate models into batch and real time decision systems
- Monitor model performance and data quality
- Prototype modeling approaches and run offline experiments
Perks/Benefits
- Comprehensive health benefits
- Dental coverage
- Employee stock purchase plan
- Flexible spending allowance
- Professional growth opportunities
- Remote-first work environment
- Supportive inclusive workplace
- Vacation and holiday programs
- Vision coverage
Skills/Tech-stack
Airflow | CatBoost | Dask | Data Quality | Feature Engineering | Fraud Detection | Kubeflow | LightGBM | MLflow | Machine Learning | Model Monitoring | PyTorch | Python | Ray | Real Time | Real-time Systems | Spark | Time Systems | XGBoost
Education
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